ScreenIT
The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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Forecasting Covid-19 Dynamics in Brazil: A Data Driven Approach
This article has 8 authors:Reviewed by ScreenIT
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COVID-19 genomic susceptibility: Definition of ACE2 variants relevant to human infection with SARS-CoV-2 in the context of ACMG/AMP Guidance
This article has 2 authors:Reviewed by ScreenIT
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Perceived versus proven SARS-CoV-2-specific immune responses in health-care professionals
This article has 7 authors:Reviewed by ScreenIT
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Cardiac Structural and Functional Characteristics in Patients with Coronavirus Disease 2019: A Serial Echocardiographic Study
This article has 11 authors:Reviewed by ScreenIT
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A Proposed Randomized, Double Blind, Placebo Controlled Study Evaluating Doxycycline for the Prevention of COVID-19 Infection and Disease In Healthcare Workers with Ongoing High Risk Exposure to COVID-19
This article has 3 authors:Reviewed by ScreenIT
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A stochastic, individual-based model for the evaluation of the impact of non-pharmacological interventions on COVID-19 transmission in Slovakia
This article has 3 authors:Reviewed by ScreenIT
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Internet-based tool for visualizing county and state level COVID-19 trends in the United States
This article has 4 authors:Reviewed by ScreenIT
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Progression of COVID-19 in Indian States - Forecasting Endpoints Using SIR and Logistic Growth Models
This article has 2 authors:Reviewed by ScreenIT
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Differential impact of physical distancing strategies on social contacts relevant for the spread of SARS-CoV-2: evidence from a cross-national online survey, March–April 2020
This article has 7 authors:Reviewed by ScreenIT